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Friday, April 24 • 4:00pm - 4:40pm
Relation Extraction using Distant Supervision, SVMs, and Probabilistic First Order Logic

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Why do we want information? So that we can use it? So that our computers can use it? When we have access to rich, structured information we can make advanced applications that solve real-world pain points.

In this talk, I'll present an effective approach for automatically creating knowledge bases: databases of factual, general information. This relation extraction approach centers around the idea that we can use machine learning and natural language processing to automatically recognize information as it exists in real-world, unstructured text.

I'll cover the NLP tools, special ML considerations, and novel methods for creating a successful end-to-end relation extraction system. I will also cover experimental results with this system architecture in both big-data and a search-oriented environments.


Malcolm Greaves

Software engineer at Nitro. Works on crafting solutions to large-scale machine learning and natural language processing problems. Practitioner of functional programming practices. Keeps up to date with latest published algorithms and ideas, innovation through hacking novel solutions, and a master bug squasher. Formally, received both my Bachelor's ('13) and Master's ('14) of Computer Science from Carnegie Mellon University. During his... Read More →

Friday April 24, 2015 4:00pm - 4:40pm